AI Agent Learning

This project is a learning exploration of how Large Language Models (LLMs) can be extended into AI agents capable of using external tools. It is not a production system—instead, it demonstrates the core building blocks of an AI agent.

Core Concepts

• LLM as the Core Brain: Using Groq API with LLaMA-3.
• Tool Integration: Calculator, file reader, time fetcher, web search, and email sender.
• Agent Loop: The LLM decides when to call tools, executes them, and returns the results.

Project Structure

Ai-Agent-Learning-main/
│── Notes/
│   ├── How_LLM_Works.md
│   ├── What_is_ai_agents.md
│
│── tool_use_agent/
│   ├── main.py
│   ├── agent.py
│   ├── tools.py
│   └── Readme.md
            

Key Features

• LLM Integration: Chat completions with system and user prompts via Groq API and LLaMA-3.
• Tool-Use Demonstrations: Includes a calculator, time fetcher, file reader, web search (SerpAPI), and email sending (SMTP).
• Agent Orchestration: The LLM decides which tools to call, parses arguments, executes, and returns the output.